• 제목/요약/키워드: sequential empirical process

검색결과 17건 처리시간 0.027초

THE EMPIRICAL LIL FOR THE KAPLAN-MEIER INTEGRAL PROCESS

  • Bae, Jong-Sig;Kim, Sung-Yeun
    • 대한수학회보
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    • 제40권2호
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    • pp.269-279
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    • 2003
  • We prove an empirical LIL for the Kaplan-Meier integral process constructed from the random censorship model under bracketing entropy and mild assumptions due to censoring effects. The main method in deriving the empirical LIL is to use a weak convergence result of the sequential Kaplan-Meier integral process whose proofs appear in Bae and Kim [2]. Using the result of weak convergence, we translate the problem of the Kaplan Meier integral process into that of a Gaussian process. Finally we derive the result using an empirical LIL for the Gaussian process of Pisier [6] via a method adapted from Ossiander [5]. The result of this paper extends the empirical LIL for IID random variables to that of a random censorship model.

THE LAWS OF THE ITERATED LOGARITHM FOR THE TENT MAP

  • Bae, Jongsig;Hwang, Changha;Jun, Doobae
    • 대한수학회논문집
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    • 제32권4호
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    • pp.1067-1076
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    • 2017
  • This paper considers the asymptotic behaviors of the processes generated by the classical ergodic tent map that is defined on the unit interval. We develop a sequential empirical process and get the uniform version of law of iterated logarithm for the tent map by using the bracketing entropy method.

통계적모델을 이용한 원자로냉각재펌프 밀봉장치 성능감시 (Reactor Coolant Pump Seal Monitoring System Using Statistical Modeling Techniques)

  • 이송규;정장규;배종길;안상하
    • 한국소음진동공학회:학술대회논문집
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    • 한국소음진동공학회 2007년도 추계학술대회논문집
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    • pp.1386-1390
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    • 2007
  • This paper presents the equipment condition monitoring technology for the process or the equipment using statistical techniques. The equipment condition monitoring system consists of an empirical model to estimate the expected sensor values of process variables and a diagnose model to detect the abnormal condition and to identify the root source of the problem. The empirical model is constructed by the analysis of historic data. The diagnose model uses the sequential probability ratio test (SPRT) technique. The monitoring system was tested with real operating data acquired from the Reactor Coolant Pump Seal in the Nuclear Power Plant. It can detect the system degradation or failure at the early stage since it is able to catch the subtle deviation of process variables from normal condition.

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THE SEQUENTIAL UNIFORM LAW OF LARGE NUMBERS

  • Bae, Jong-Sig;Kim, Sung-Yeun
    • 대한수학회보
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    • 제43권3호
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    • pp.479-486
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    • 2006
  • Let $Z_n(s,\;f)=n^{-1}\;{\sum}^{ns}_{i=1}(f(X_i)-Pf)$ be the sequential empirical process based on the independent and identically distributed random variables. We prove that convergence problems of $sup_{(s,\;f)}|Z_n(s,\;f)|$ to zero boil down to those of $sup_f|Z_n(1,\;f)|$. We employ Ottaviani's inequality and the complete convergence to establish, under bracketing entropy with the second moment, the almost sure convergence of $sup_{(s,\;f)}|Z_n(s,\;f)|$ to zero.

SAHN 모델의 부분적 패턴 추정 방법에 대한 연구 (A Study on Partial Pattern Estimation for Sequential Agglomerative Hierarchical Nested Model)

  • 장경원;안태천
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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    • pp.143-145
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    • 2005
  • In this paper, an empirical study result on pattern estimation method is devoted to reveal underlying data patterns with a relatively reduced computational cost. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). Conventional SAHN based clustering requires large computation time in the initial step of algorithm. To deal with this concern, we modified overall process with a partial approach. In the beginning of this method, we divide given data set to several sub groups with uniform sampling and then each divided sub data group is applied to SAHN based method. The advantage of this method reduces computation time of original process and gives similar results. Proposed is applied to several test data set and simulation result with conceptual analysis is presented.

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Development of ICT as an evolutionary process

  • Hwang, Gyu-hee
    • 기술혁신학회지
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    • 제5권2호
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    • pp.189-211
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    • 2002
  • The research shows how the technological change of 'Information and Communication Technology' (ICT) is accompanied with the usage change. It aims to provide a better conceptualization with empirical findings about the fact that the technological development of ICT is a convergence process of ICT factors with the usage of ICT moving from a limited coverage toward a general-purpose. The research adapts a descriptive methodology on a historical matter and demonstrates how it can be conducted through analytical description of Input-Output tables (I/O) the over periods. The case is about the UK with sequential I/O during 1970s- 90s.

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거주지 이동에 관한 모형의 설정-거시적 접근과 미시적 접근의 결합 (Migration Decision-Making Process-Synthesis of Macrolevel and Microlevel Perspectives)

  • 정기원
    • 한국인구학
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    • 제12권1호
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    • pp.30-42
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    • 1989
  • This study develops a model of migration decision-making process, with identifying macrolevel and microlevel factors affecting the process. The model includes some sequential stages : to be dissatisfied with current residential area, intend to move, collect information about alternative destinations, select destination, decide to move, and make actual migration. The macrolevel factors included in the model are environmental, socioeconomic, cultural, and demographic characteristics of the current residence and alternative destinations. The microlevel factors are psychological, socioeconomic, and demographic characteristics of the individual. The effects of the macrolevel and microlevel factors on each stage of migration decision-making process are identified from the previous studies on migration. This study has both theoretical and practical implications. The theoretical contribution will be in the area of integrating the ecological and the individual level perspectives of migration by identifying the macrolevel and microlevel effects on migration decision-making process. This study also has implications for theoretical frameworks guiding empirical analysis of migration behavior of the individuals, and for policies aimed at redistributing population.

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THE UNIFORM CLT FOR MARTINGALE DIFFERENCE ARRAYS UNDER THE UNIFORMLY INTEGRABLE ENTROPY

  • Bae, Jong-Sig;Jun, Doo-Bae;Levental, Shlomo
    • 대한수학회보
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    • 제47권1호
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    • pp.39-51
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    • 2010
  • In this paper we consider the uniform central limit theorem for a martingale-difference array of a function-indexed stochastic process under the uniformly integrable entropy condition. We prove a maximal inequality for martingale-difference arrays of process indexed by a class of measurable functions by a method as Ziegler [19] did for triangular arrays of row wise independent process. The main tools are the Freedman inequality for the martingale-difference and a sub-Gaussian inequality based on the restricted chaining. The results of present paper generalizes those of Ziegler [19] and other results of independent problems. The results also generalizes those of Bae and Choi [3] to martingale-difference array of a function-indexed stochastic process. Finally, an application to classes of functions changing with n is given.

Data Pattern Estimation with Movement of the Center of Gravity

  • Ahn Tae-Chon;Jang Kyung-Won;Shin Dong-Du;Kang Hak-Soo;Yoon Yang-Woong
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권3호
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    • pp.210-216
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    • 2006
  • In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.